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Neuron Net
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Class of convolution layer. More...
Public Member Functions | |
CNeuronConv () | |
Constructor. More... | |
~CNeuronConv (void) | |
Destructor. More... | |
virtual bool | calcInputGradients (CLayer *prevLayer) |
Method to transfer gradients to previous layer. More... | |
virtual bool | calcInputGradients (CNeuronBase *prevNeuron, uint index) |
Method to transfer gradients to neuron in previous layer. More... | |
virtual double | activationFunctionDerivative (double x) |
Calculate derivative of activation function. More... | |
virtual int | Type (void) const |
Identificator of class. More... | |
virtual bool | Save (int const file_handle) |
Save method. More... | |
virtual bool | Load (int const file_handle) |
Load method. More... | |
virtual bool | feedForward (CObject *&SourceObject) |
Dispatch method for defining the subroutine for Feed Forward process. More... | |
virtual bool | calcHiddenGradients (CObject *&TargetObject) |
Dispatch method for defining the subroutine for transfer gradient to previous layer. More... | |
virtual bool | Init (uint numOutputs, uint myIndex, int window, int step, int units_count, ENUM_OPTIMIZATION optimization_type) |
Method of initialization class. More... | |
virtual bool | Init (uint numOutputs, uint myIndex, ENUM_OPTIMIZATION optimization_type) |
Method of initialization class. More... | |
virtual CLayer * | getOutputLayer (void) |
Method for getting a pointer to the resulting neural layer. Not used in fully connected neural networks. More... | |
virtual bool | updateInputWeights (CObject *&SourceObject) |
Dispatch method for defining the subroutine for updating weights. More... | |
virtual void | SetActivationFunction (ENUM_ACTIVATION value) |
Set the type of activation function (ENUM_ACTIVATION) More... | |
virtual void | setOutputVal (double val) |
Set the output value. More... | |
virtual double | getOutputVal () |
Return result of feed forward operations. More... | |
virtual double | getPrevVal () |
Return result of feed forward operations at previous iteration. More... | |
virtual void | setGradient (double val) |
Set gradient value to neuron. More... | |
virtual double | getGradient () |
Return gradient of neuron. More... | |
virtual CArrayCon * | getConnections () |
Method to get access to array of connections. More... | |
virtual double | SigmoidFunctionDerivative (double x) |
Calculate derivative of Sigmoid function. More... | |
virtual double | TanhFunctionDerivative (double x) |
Calculate derivative of \(tanh(x)\). More... | |
Static Public Attributes | |
static double | alpha =0.8 |
Multiplier to momentum in SGD optimization. More... | |
Protected Member Functions | |
virtual bool | feedForward (CLayer *prevLayer) |
Feed Forward method. More... | |
virtual bool | calcHiddenGradients (CLayer *&nextLayer) |
Method to transfer gradient to previous layer. More... | |
virtual double | activationFunction (double x) |
Method to calculate activation function. More... | |
virtual bool | updateInputWeights (CLayer *&prevLayer) |
Method for updating weights. More... | |
virtual double | SigmoidFunction (double x) |
Calculating Sigmoid \(\frac{1}{1+e^x}\). More... | |
virtual double | TanhFunction (double x) |
Calculating \(tanh(x)\). More... | |
Protected Attributes | |
double | param |
CLayer * | OutputLayer |
Layer of output data. Used for connection with next layer. More... | |
int | iWindow |
Input window size. More... | |
int | iStep |
Size of step. More... | |
double | outputVal |
Output value. More... | |
double | prevVal |
Previous output value. More... | |
uint | m_myIndex |
Index of neuron in layer. More... | |
double | gradient |
Current gradient of neuron. More... | |
CArrayCon * | Connections |
Array of connections with neurons in next layer. More... | |
ENUM_ACTIVATION | activation |
Activation type (ENUM_ACTIVATION) More... | |
ENUM_OPTIMIZATION | optimization |
Optimization method (ENUM_OPTIMIZATION) More... | |
int | t |
Count of iterations. More... | |
Class of convolution layer.
Detailed description on the link.
Definition at line 832 of file NeuroNet.mqh.
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inline |
Constructor.
Definition at line 841 of file NeuroNet.mqh.
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inline |
Destructor.
Definition at line 842 of file NeuroNet.mqh.
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protectedvirtual |
Method to calculate activation function.
x | Input data. |
Reimplemented from CNeuronBase.
Definition at line 946 of file NeuroNet.mqh.
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virtual |
Calculate derivative of activation function.
[in] | x | Input data |
Reimplemented from CNeuronBase.
Definition at line 1024 of file NeuroNet.mqh.
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protectedvirtual |
Method to transfer gradient to previous layer.
nextLayer | Pointer to next layer. |
Reimplemented from CNeuronProof.
Definition at line 1004 of file NeuroNet.mqh.
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virtualinherited |
Dispatch method for defining the subroutine for transfer gradient to previous layer.
TargetObject | Pointer to next layer. |
Definition at line 955 of file NeuroNet.mqh.
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virtual |
Method to transfer gradients to previous layer.
[in] | prevLayer | Pointer to previous layer. |
Reimplemented from CNeuronProof.
Definition at line 1227 of file NeuroNet.mqh.
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virtual |
Method to transfer gradients to neuron in previous layer.
[in] | prevNeuron | Pointer to neuron. |
[in] | index | Index of neuron in previous layer |
Reimplemented from CNeuronProof.
Definition at line 1271 of file NeuroNet.mqh.
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protectedvirtual |
Feed Forward method.
prevLayer | Pointer to previos layer. |
Reimplemented from CNeuronProof.
Definition at line 912 of file NeuroNet.mqh.
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virtualinherited |
Dispatch method for defining the subroutine for Feed Forward process.
SourceObject | Pointer to previos layer. |
Definition at line 855 of file NeuroNet.mqh.
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inlinevirtualinherited |
Method to get access to array of connections.
Definition at line 439 of file NeuroNet.mqh.
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inlinevirtualinherited |
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inlinevirtualinherited |
Method for getting a pointer to the resulting neural layer. Not used in fully connected neural networks.
Reimplemented from CNeuronBase.
Reimplemented in CNeuronLSTM.
Definition at line 819 of file NeuroNet.mqh.
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inlinevirtualinherited |
Return result of feed forward operations.
Definition at line 435 of file NeuroNet.mqh.
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inlinevirtualinherited |
Return result of feed forward operations at previous iteration.
Definition at line 436 of file NeuroNet.mqh.
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virtualinherited |
Method of initialization class.
numOutputs | Number of connections to next layer. |
myIndex | Index of neuron in layer. |
optimization_type | Optimization type (ENUM_OPTIMIZATION) |
Definition at line 484 of file NeuroNet.mqh.
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virtualinherited |
Method of initialization class.
numOutputs | Number of connections to next layer. |
myIndex | Index of neuron in layer. |
window | Size of input window |
step | Step size. |
units_countNumber | of neurons. |
optimization_type | Optimization type (ENUM_OPTIMIZATION) |
Reimplemented in CNeuronLSTM.
Definition at line 1072 of file NeuroNet.mqh.
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virtual |
Load method.
[in] | file_handle | handle of file |
Reimplemented from CNeuronProof.
Definition at line 2107 of file NeuroNet.mqh.
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virtual |
Save method.
[in] | file_handle | handle of file |
Reimplemented from CNeuronProof.
Definition at line 2095 of file NeuroNet.mqh.
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inlinevirtualinherited |
Set the type of activation function (ENUM_ACTIVATION)
Definition at line 429 of file NeuroNet.mqh.
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inlinevirtualinherited |
Set gradient value to neuron.
Definition at line 437 of file NeuroNet.mqh.
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inlinevirtualinherited |
Set the output value.
Definition at line 434 of file NeuroNet.mqh.
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inlineprotectedvirtualinherited |
Calculating Sigmoid \(\frac{1}{1+e^x}\).
x | Input data. |
Definition at line 422 of file NeuroNet.mqh.
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inlinevirtualinherited |
Calculate derivative of Sigmoid function.
x | Input data |
Definition at line 441 of file NeuroNet.mqh.
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inlineprotectedvirtualinherited |
Calculating \(tanh(x)\).
x | Input data. |
Definition at line 423 of file NeuroNet.mqh.
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inlinevirtualinherited |
Calculate derivative of \(tanh(x)\).
x | Input data |
Definition at line 442 of file NeuroNet.mqh.
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inlinevirtual |
Identificator of class.
Reimplemented from CNeuronProof.
Definition at line 847 of file NeuroNet.mqh.
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protectedvirtual |
Method for updating weights.
prevLayer | Pointer to previos layer. |
Reimplemented from CNeuronBase.
Definition at line 1033 of file NeuroNet.mqh.
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virtualinherited |
Dispatch method for defining the subroutine for updating weights.
SourceObject | Pointer to previos layer. |
Definition at line 883 of file NeuroNet.mqh.
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protectedinherited |
Activation type (ENUM_ACTIVATION)
Definition at line 414 of file NeuroNet.mqh.
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staticinherited |
Multiplier to momentum in SGD optimization.
Definition at line 432 of file NeuroNet.mqh.
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protectedinherited |
Array of connections with neurons in next layer.
Definition at line 413 of file NeuroNet.mqh.
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protectedinherited |
Current gradient of neuron.
Definition at line 412 of file NeuroNet.mqh.
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protectedinherited |
Size of step.
Definition at line 808 of file NeuroNet.mqh.
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protectedinherited |
Input window size.
Definition at line 807 of file NeuroNet.mqh.
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protectedinherited |
Index of neuron in layer.
Definition at line 411 of file NeuroNet.mqh.
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protectedinherited |
Optimization method (ENUM_OPTIMIZATION)
Definition at line 415 of file NeuroNet.mqh.
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protectedinherited |
Layer of output data. Used for connection with next layer.
Definition at line 806 of file NeuroNet.mqh.
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protectedinherited |
Output value.
Definition at line 409 of file NeuroNet.mqh.
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protected |
Definition at line 835 of file NeuroNet.mqh.
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protectedinherited |
Previous output value.
Definition at line 410 of file NeuroNet.mqh.
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protectedinherited |
Count of iterations.
Definition at line 416 of file NeuroNet.mqh.